.TH std::experimental::parallel::reduce 3 "2024.06.10" "http://cppreference.com" "C++ Standard Libary"
.SH NAME
std::experimental::parallel::reduce \- std::experimental::parallel::reduce

.SH Synopsis
   Defined in header <experimental/numeric>
   template< class InputIt >

   typename std::iterator_traits<InputIt>::value_type reduce(      \fB(1)\fP (parallelism TS)

       InputIt first, InputIt last );
   template< class ExecutionPolicy, class InputIterator >

   typename std::iterator_traits<InputIt>::value_type reduce(      \fB(2)\fP (parallelism TS)

       ExecutionPolicy&& policy, InputIt first, InputIt last );
   template< class InputIt, class T >                              \fB(3)\fP (parallelism TS)
   T reduce( InputIt first, InputIt last, T init );
   template< class ExecutionPolicy, class InputIt, class T >
   T reduce( ExecutionPolicy&& policy, InputIt first, InputIt      \fB(4)\fP (parallelism TS)
   last, T init );
   template< class InputIt, class T, class BinaryOp >
   T reduce( InputIt first, InputIt last, T init, BinaryOp         \fB(5)\fP (parallelism TS)
   binary_op );
   template< class ExecutionPolicy, class InputIt, class T, class
   BinaryOp >

   T reduce( ExecutionPolicy&& policy,                             \fB(6)\fP (parallelism TS)

             InputIt first, InputIt last, T init, BinaryOp
   binary_op );

   1) Same as reduce(first, last, typename
   std::iterator_traits<InputIt>::value_type{}).
   3) Same as reduce(first, last, init, std::plus<>()).
   5) Reduces the range [first, last), possibly permuted and aggregated in unspecified
   manner, along with the initial value init over binary_op.
   2,4,6) Same as (1,3,5), but executed according to policy.

   The behavior is non-deterministic if binary_op is not associative or not
   commutative.

   The behavior is undefined if binary_op modifies any element or invalidates any
   iterator in [first, last).

.SH Parameters

   first, last - the range of elements to apply the algorithm to
   init        - the initial value of the generalized sum
   policy      - the execution policy
                 binary FunctionObject that will be applied in unspecified order to the
   binary_op   - result of dereferencing the input iterators, the results of other
                 binary_op and init
.SH Type requirements
   -
   InputIt must meet the requirements of LegacyInputIterator.

.SH Return value

   Generalized sum of init and *first, *(first + 1), ... *(last - 1) over binary_op,

   where generalized sum GSUM(op, a
   1, ..., a
   N) is defined as follows:

     * if N=1, a
       1
     * if N > 1, op(GSUM(op, b
       1, ..., b
       K), GSUM(op, b
       M, ..., b
       N)) where

     * b
       1, ..., b
       N may be any permutation of a1, ..., aN and
     * 1 < K+1 = M ≤ N

   in other words, the elements of the range may be grouped and rearranged in arbitrary
   order.

.SH Complexity

   O(last - first) applications of binary_op.

.SH Exceptions

     * If execution of a function invoked as part of the algorithm throws an exception,

     * if policy is parallel_vector_execution_policy, std::terminate is called.
     * if policy is sequential_execution_policy or parallel_execution_policy, the
       algorithm exits with an exception_list containing all uncaught exceptions. If
       there was only one uncaught exception, the algorithm may rethrow it without
       wrapping in exception_list. It is unspecified how much work the algorithm will
       perform before returning after the first exception was encountered.
     * if policy is some other type, the behavior is implementation-defined.
     * If the algorithm fails to allocate memory (either for itself or to construct an
       exception_list when handling a user exception), std::bad_alloc is thrown.

.SH Notes

   If the range is empty, init is returned, unmodified.

     * If policy is an instance of sequential_execution_policy, all operations are
       performed in the calling thread.
     * If policy is an instance of parallel_execution_policy, operations may be
       performed in unspecified number of threads, indeterminately sequenced with each
       other.
     * If policy is an instance of parallel_vector_execution_policy, execution may be
       both parallelized and vectorized: function body boundaries are not respected and
       user code may be overlapped and combined in arbitrary manner (in particular,
       this implies that a user-provided Callable must not acquire a mutex to access a
       shared resource).

.SH Example

   reduce is the out-of-order version of std::accumulate:


// Run this code

 #include <chrono>
 #include <experimental/execution_policy>
 #include <experimental/numeric>
 #include <iostream>
 #include <numeric>
 #include <vector>

 int main()
 {
     std::vector<double> v(10'000'007, 0.5);

     {
         auto t1 = std::chrono::high_resolution_clock::now();
         double result = std::accumulate(v.begin(), v.end(), 0.0);
         auto t2 = std::chrono::high_resolution_clock::now();
         std::chrono::duration<double, std::milli> ms = t2 - t1;
         std::cout << std::fixed << "std::accumulate result " << result
                   << " took " << ms.count() << " ms\\n";
     }

     {
         auto t1 = std::chrono::high_resolution_clock::now();
         double result = std::experimental::parallel::reduce(
                             std::experimental::parallel::par,
                             v.begin(), v.end());
         auto t2 = std::chrono::high_resolution_clock::now();
         std::chrono::duration<double, std::milli> ms = t2 - t1;
         std::cout << "parallel::reduce result "
                   << result << " took " << ms.count() << " ms\\n";
     }
 }

.SH Possible output:

 std::accumulate result 5000003.50000 took 12.7365 ms
 parallel::reduce result 5000003.50000 took 5.06423 ms

.SH See also

   accumulate       sums up or folds a range of elements
                    \fI(function template)\fP
                    applies a function to a range of elements, storing results in a
   transform        destination range
                    \fI(function template)\fP
   transform_reduce applies a functor, then reduces out of order
   (parallelism TS) \fI(function template)\fP
